Skip to the main content

Preliminary communication

https://doi.org/10.7307/ptt.v29i1.2076

A Modified Decomposed Theory of Planned Behaviour Model to Analyze User Intention towards Distance-Based Electronic Toll Collection Services

Chi-Chung Tao ; Tamkang University
Chieh-Chih Fan ; Tamkang University


Full text: english PDF 384 Kb

page 85-97

downloads: 2.009

cite


Abstract

This study proposes a modified decomposed theory of planned behaviour model (DTPB) that integrates satisfaction and trust into the original DTPB model to explore what kind of factors affect the user intention towards distance-based electronic toll collection (ETC) services. The proposed model is empirically tested by using data collected from a questionnaire survey with a computer assisted telephone interview system. Empirical analysis is carried out in three stages that combine confirmatory factor analysis, structural equation modelling (SEM), and Bayesian network: (1) examination of reliability and validity of the measurement model; (2) analysis of structural model; (3) prediction of the probability of user intention change based on rigorous framework of SEM. The results confirm that the satisfaction and trust have positive effects on the behaviour intention, also validating that five constructs have indirect effects on the behaviour intention through attitude and perceived behaviour control. Compatibility is the most important influence factor, followed by perceived usefulness, facilitating conditions, self-efficacy, and perceived ease of use. The findings of this study identify potential improvements for ETC operator, such as contributing to the society to enhance the company image and trust of enterprise with charity activities, and simultaneously upgrading the information platform of website, software, and Apps.

Keywords

decomposed theory of planned behaviour; structural equation modelling; Bayesian network; distance-based electronic toll collection

Hrčak ID:

179576

URI

https://hrcak.srce.hr/179576

Publication date:

3.2.2017.

Visits: 3.107 *